Overview

Dataset statistics

Number of variables17
Number of observations951
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory176.5 KiB
Average record size in memory190.0 B

Variable types

Categorical2
Numeric15

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
name has a high cardinality: 447 distinct valuesHigh cardinality
Jitter(%) is highly overall correlated with Jitter(Abs) and 6 other fieldsHigh correlation
Jitter(Abs) is highly overall correlated with Jitter(%) and 6 other fieldsHigh correlation
Jitter:RAP is highly overall correlated with Jitter(%) and 5 other fieldsHigh correlation
Jitter:PPQ is highly overall correlated with Jitter(%) and 6 other fieldsHigh correlation
Jitter:DDP is highly overall correlated with Jitter(%) and 5 other fieldsHigh correlation
Shimmer is highly overall correlated with Shimmer(dB) and 5 other fieldsHigh correlation
Shimmer(dB) is highly overall correlated with Shimmer and 6 other fieldsHigh correlation
Shimmer:APQ3 is highly overall correlated with Shimmer and 5 other fieldsHigh correlation
Shimmer:APQ5 is highly overall correlated with Shimmer and 5 other fieldsHigh correlation
Shimmer:DDA is highly overall correlated with Shimmer and 5 other fieldsHigh correlation
NHR is highly overall correlated with Jitter(%) and 9 other fieldsHigh correlation
HNR is highly overall correlated with Shimmer and 6 other fieldsHigh correlation
RPDE is highly overall correlated with Jitter(%) and 7 other fieldsHigh correlation
PPE is highly overall correlated with Jitter(%) and 4 other fieldsHigh correlation
name is uniformly distributedUniform

Reproduction

Analysis started2023-03-31 11:09:51.108298
Analysis finished2023-03-31 11:10:32.167889
Duration41.06 seconds
Software versionpandas-profiling vv3.6.2
Download configurationconfig.json

Variables

name
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct447
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size57.6 KiB
70
 
3
152
 
3
192
 
3
45
 
3
18
 
3
Other values (442)
936 

Length

Max length14
Median length3
Mean length4.9085174
Min length1

Characters and Unicode

Total characters4668
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)20.5%

Sample

1st rowphon_R01_S01_1
2nd rowphon_R01_S01_2
3rd rowphon_R01_S01_3
4th rowphon_R01_S01_4
5th rowphon_R01_S01_5

Common Values

ValueCountFrequency (%)
70 3
 
0.3%
152 3
 
0.3%
192 3
 
0.3%
45 3
 
0.3%
18 3
 
0.3%
171 3
 
0.3%
44 3
 
0.3%
80 3
 
0.3%
32 3
 
0.3%
140 3
 
0.3%
Other values (437) 921
96.8%

Length

2023-03-31T16:40:32.277066image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
70 3
 
0.3%
92 3
 
0.3%
158 3
 
0.3%
203 3
 
0.3%
130 3
 
0.3%
249 3
 
0.3%
104 3
 
0.3%
59 3
 
0.3%
1 3
 
0.3%
135 3
 
0.3%
Other values (437) 921
96.8%

Most occurring characters

ValueCountFrequency (%)
1 750
16.1%
_ 585
12.5%
2 421
 
9.0%
0 393
 
8.4%
3 258
 
5.5%
4 245
 
5.2%
5 198
 
4.2%
h 195
 
4.2%
R 195
 
4.2%
n 195
 
4.2%
Other values (7) 1233
26.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2913
62.4%
Lowercase Letter 780
 
16.7%
Connector Punctuation 585
 
12.5%
Uppercase Letter 390
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 750
25.7%
2 421
14.5%
0 393
13.5%
3 258
 
8.9%
4 245
 
8.4%
5 198
 
6.8%
6 185
 
6.4%
7 163
 
5.6%
9 153
 
5.3%
8 147
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
h 195
25.0%
n 195
25.0%
o 195
25.0%
p 195
25.0%
Uppercase Letter
ValueCountFrequency (%)
R 195
50.0%
S 195
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 585
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3498
74.9%
Latin 1170
 
25.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 750
21.4%
_ 585
16.7%
2 421
12.0%
0 393
11.2%
3 258
 
7.4%
4 245
 
7.0%
5 198
 
5.7%
6 185
 
5.3%
7 163
 
4.7%
9 153
 
4.4%
Latin
ValueCountFrequency (%)
h 195
16.7%
R 195
16.7%
n 195
16.7%
o 195
16.7%
S 195
16.7%
p 195
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 750
16.1%
_ 585
12.5%
2 421
 
9.0%
0 393
 
8.4%
3 258
 
5.5%
4 245
 
5.2%
5 198
 
4.2%
h 195
 
4.2%
R 195
 
4.2%
n 195
 
4.2%
Other values (7) 1233
26.4%

Jitter(%)
Real number (ℝ)

Distinct478
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0031232981
Minimum0.00021
Maximum0.03316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:32.382237image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.00021
5-th percentile0.00061
Q10.00111
median0.00196
Q30.0037
95-th percentile0.00872
Maximum0.03316
Range0.03295
Interquartile range (IQR)0.00259

Descriptive statistics

Standard deviation0.0035728769
Coefficient of variation (CV)1.1439436
Kurtosis19.613359
Mean0.0031232981
Median Absolute Deviation (MAD)0.00104
Skewness3.6705415
Sum2.9702565
Variance1.2765449 × 10-5
MonotonicityNot monotonic
2023-03-31T16:40:32.497202image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00076 9
 
0.9%
0.00106 8
 
0.8%
0.00126 8
 
0.8%
0.00128 8
 
0.8%
0.00117 8
 
0.8%
0.00141 7
 
0.7%
0.00145 7
 
0.7%
0.00086 7
 
0.7%
0.00189 7
 
0.7%
0.00104 6
 
0.6%
Other values (468) 876
92.1%
ValueCountFrequency (%)
0.00021 1
 
0.1%
0.00023 1
 
0.1%
0.00027 1
 
0.1%
0.00037 3
0.3%
0.00038 1
 
0.1%
0.00039 2
0.2%
0.00041 1
 
0.1%
0.00042 2
0.2%
0.00044 2
0.2%
0.00046 2
0.2%
ValueCountFrequency (%)
0.03316 1
0.1%
0.03107 1
0.1%
0.03011 1
0.1%
0.02775 1
0.1%
0.02714 1
0.1%
0.0201 1
0.1%
0.01989 1
0.1%
0.01936 1
0.1%
0.01872 1
0.1%
0.01854 1
0.1%

Jitter(Abs)
Real number (ℝ)

Distinct560
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2316338 × 10-5
Minimum6.86 × 10-7
Maximum0.00026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:32.603261image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum6.86 × 10-7
5-th percentile2.665 × 10-6
Q16.025 × 10-6
median1.18 × 10-5
Q32.935 × 10-5
95-th percentile7.875 × 10-5
Maximum0.00026
Range0.000259314
Interquartile range (IQR)2.3325 × 10-5

Descriptive statistics

Standard deviation2.8024651 × 10-5
Coefficient of variation (CV)1.2557908
Kurtosis17.482519
Mean2.2316338 × 10-5
Median Absolute Deviation (MAD)7.66 × 10-6
Skewness3.4198447
Sum0.021222837
Variance7.8538106 × 10-10
MonotonicityNot monotonic
2023-03-31T16:40:32.717386image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 × 10-547
 
4.9%
4 × 10-528
 
2.9%
2 × 10-528
 
2.9%
1 × 10-520
 
2.1%
5 × 10-517
 
1.8%
6 × 10-516
 
1.7%
1.39 × 10-510
 
1.1%
8 × 10-59
 
0.9%
7 × 10-58
 
0.8%
1.03 × 10-57
 
0.7%
Other values (550) 761
80.0%
ValueCountFrequency (%)
6.86 × 10-71
0.1%
7.76 × 10-71
0.1%
9.28 × 10-71
0.1%
1.14 × 10-61
0.1%
1.18 × 10-61
0.1%
1.26 × 10-61
0.1%
1.27 × 10-61
0.1%
1.28 × 10-61
0.1%
1.36 × 10-61
0.1%
1.44 × 10-61
0.1%
ValueCountFrequency (%)
0.00026 1
0.1%
0.00025648 1
0.1%
0.00022 1
0.1%
0.000179232 1
0.1%
0.000165706 1
0.1%
0.000161542 1
0.1%
0.00016 1
0.1%
0.000152676 1
0.1%
0.00015 2
0.2%
0.00014 1
0.1%

Jitter:RAP
Real number (ℝ)

Distinct306
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0011589115
Minimum2 × 10-5
Maximum0.02144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:32.839635image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum2 × 10-5
5-th percentile8 × 10-5
Q10.00018
median0.00044
Q30.001395
95-th percentile0.004165
Maximum0.02144
Range0.02142
Interquartile range (IQR)0.001215

Descriptive statistics

Standard deviation0.0019374694
Coefficient of variation (CV)1.671801
Kurtosis32.220182
Mean0.0011589115
Median Absolute Deviation (MAD)0.00032
Skewness4.6514439
Sum1.1021248
Variance3.7537876 × 10-6
MonotonicityNot monotonic
2023-03-31T16:40:33.302265image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00012 24
 
2.5%
0.00014 23
 
2.4%
0.00015 22
 
2.3%
9 × 10-520
 
2.1%
0.0002 20
 
2.1%
0.00011 19
 
2.0%
0.00013 19
 
2.0%
8 × 10-518
 
1.9%
0.00016 17
 
1.8%
0.00027 17
 
1.8%
Other values (296) 752
79.1%
ValueCountFrequency (%)
2 × 10-52
 
0.2%
3 × 10-52
 
0.2%
4 × 10-54
 
0.4%
5 × 10-511
1.2%
6 × 10-59
0.9%
7 × 10-514
1.5%
8 × 10-518
1.9%
9 × 10-520
2.1%
0.0001 14
1.5%
0.00011 19
2.0%
ValueCountFrequency (%)
0.02144 1
0.1%
0.01854 1
0.1%
0.018 1
0.1%
0.01568 1
0.1%
0.01159 1
0.1%
0.01117 1
0.1%
0.01105 1
0.1%
0.01075 1
0.1%
0.00996 1
0.1%
0.00928 1
0.1%

Jitter:PPQ
Real number (ℝ)

Distinct356
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0016279902
Minimum5 × 10-5
Maximum0.01958
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:33.407294image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum5 × 10-5
5-th percentile0.00021
Q10.00045
median0.00086
Q30.00194
95-th percentile0.00517
Maximum0.01958
Range0.01953
Interquartile range (IQR)0.00149

Descriptive statistics

Standard deviation0.0021546471
Coefficient of variation (CV)1.3235013
Kurtosis20.222869
Mean0.0016279902
Median Absolute Deviation (MAD)0.00054
Skewness3.8245663
Sum1.5482187
Variance4.6425043 × 10-6
MonotonicityNot monotonic
2023-03-31T16:40:33.509488image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00032 14
 
1.5%
0.00034 12
 
1.3%
0.00049 12
 
1.3%
0.00024 11
 
1.2%
0.00022 11
 
1.2%
0.00021 11
 
1.2%
0.00038 11
 
1.2%
0.00033 11
 
1.2%
0.00078 10
 
1.1%
0.00035 10
 
1.1%
Other values (346) 838
88.1%
ValueCountFrequency (%)
5 × 10-51
 
0.1%
6 × 10-51
 
0.1%
7 × 10-51
 
0.1%
9 × 10-51
 
0.1%
0.0001 1
 
0.1%
0.00012 1
 
0.1%
0.00013 3
 
0.3%
0.00014 8
0.8%
0.00015 2
 
0.2%
0.00016 5
0.5%
ValueCountFrequency (%)
0.01958 1
0.1%
0.01832 1
0.1%
0.01699 1
0.1%
0.01628 1
0.1%
0.01522 1
0.1%
0.01434 1
0.1%
0.01422 1
0.1%
0.0129 1
0.1%
0.01256 1
0.1%
0.01166 1
0.1%

Jitter:DDP
Real number (ℝ)

Distinct488
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003476966
Minimum5 × 10-5
Maximum0.06433
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:33.635085image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum5 × 10-5
5-th percentile0.00024
Q10.00054
median0.00132
Q30.00419
95-th percentile0.0125
Maximum0.06433
Range0.06428
Interquartile range (IQR)0.00365

Descriptive statistics

Standard deviation0.0058125174
Coefficient of variation (CV)1.6717211
Kurtosis32.235231
Mean0.003476966
Median Absolute Deviation (MAD)0.00096
Skewness4.6523217
Sum3.3065946
Variance3.3785358 × 10-5
MonotonicityNot monotonic
2023-03-31T16:40:33.732336image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00027 11
 
1.2%
0.00036 11
 
1.2%
0.00037 10
 
1.1%
0.00042 9
 
0.9%
0.0008 9
 
0.9%
0.00054 9
 
0.9%
0.00044 9
 
0.9%
0.00015 8
 
0.8%
0.00049 8
 
0.8%
0.0006 8
 
0.8%
Other values (478) 859
90.3%
ValueCountFrequency (%)
5 × 10-51
 
0.1%
6 × 10-51
 
0.1%
8 × 10-51
 
0.1%
0.0001 1
 
0.1%
0.00011 1
 
0.1%
0.00012 1
 
0.1%
0.00013 2
 
0.2%
0.00014 1
 
0.1%
0.00015 8
0.8%
0.00016 2
 
0.2%
ValueCountFrequency (%)
0.06433 1
0.1%
0.05563 1
0.1%
0.05401 1
0.1%
0.04705 1
0.1%
0.03476 1
0.1%
0.03351 1
0.1%
0.03315 1
0.1%
0.03225 1
0.1%
0.02987 1
0.1%
0.02783 1
0.1%

Shimmer
Real number (ℝ)

Distinct907
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.059729805
Minimum0.00656
Maximum0.25101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:33.842287image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.00656
5-th percentile0.015435
Q10.029435
median0.04834
Q30.077185
95-th percentile0.143585
Maximum0.25101
Range0.24445
Interquartile range (IQR)0.04775

Descriptive statistics

Standard deviation0.042103157
Coefficient of variation (CV)0.70489359
Kurtosis2.5657613
Mean0.059729805
Median Absolute Deviation (MAD)0.02189
Skewness1.5292272
Sum56.803045
Variance0.0017726758
MonotonicityNot monotonic
2023-03-31T16:40:33.962996image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11166 2
 
0.2%
0.06033 2
 
0.2%
0.02145 2
 
0.2%
0.063 2
 
0.2%
0.03702 2
 
0.2%
0.01663 2
 
0.2%
0.06054 2
 
0.2%
0.07979 2
 
0.2%
0.07295 2
 
0.2%
0.01795 2
 
0.2%
Other values (897) 931
97.9%
ValueCountFrequency (%)
0.00656 1
0.1%
0.00954 1
0.1%
0.00958 1
0.1%
0.01015 1
0.1%
0.01022 1
0.1%
0.01024 1
0.1%
0.0103 1
0.1%
0.01033 1
0.1%
0.01043 1
0.1%
0.01064 1
0.1%
ValueCountFrequency (%)
0.25101 1
0.1%
0.22316 1
0.1%
0.22167 1
0.1%
0.22066 1
0.1%
0.22025 1
0.1%
0.21727 1
0.1%
0.21597 1
0.1%
0.21267 1
0.1%
0.21242 1
0.1%
0.21209 1
0.1%

Shimmer(dB)
Real number (ℝ)

Distinct622
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5399497
Minimum0.057
Maximum2.114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:34.082415image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.057
5-th percentile0.1375
Q10.2615
median0.431
Q30.712
95-th percentile1.2965
Maximum2.114
Range2.057
Interquartile range (IQR)0.4505

Descriptive statistics

Standard deviation0.37579228
Coefficient of variation (CV)0.69597646
Kurtosis1.8752826
Mean0.5399497
Median Absolute Deviation (MAD)0.199
Skewness1.3838797
Sum513.49217
Variance0.14121984
MonotonicityNot monotonic
2023-03-31T16:40:34.215237image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.297 5
 
0.5%
0.376 5
 
0.5%
0.205 5
 
0.5%
0.154 5
 
0.5%
0.266 5
 
0.5%
0.422 5
 
0.5%
0.406 5
 
0.5%
0.155 5
 
0.5%
0.497 5
 
0.5%
0.441 5
 
0.5%
Other values (612) 901
94.7%
ValueCountFrequency (%)
0.057 1
0.1%
0.085 2
0.2%
0.089 1
0.1%
0.09 1
0.1%
0.093 1
0.1%
0.094 1
0.1%
0.096 1
0.1%
0.097 1
0.1%
0.097 2
0.2%
0.098 1
0.1%
ValueCountFrequency (%)
2.114 1
0.1%
2.019 1
0.1%
1.935 1
0.1%
1.901 1
0.1%
1.891 1
0.1%
1.886 1
0.1%
1.862 1
0.1%
1.86 1
0.1%
1.825 1
0.1%
1.814 1
0.1%

Shimmer:APQ3
Real number (ℝ)

Distinct872
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.030538498
Minimum0.00335
Maximum0.13051
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:34.367561image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.00335
5-th percentile0.007555
Q10.014535
median0.02457
Q30.03997
95-th percentile0.075995
Maximum0.13051
Range0.12716
Interquartile range (IQR)0.025435

Descriptive statistics

Standard deviation0.021811111
Coefficient of variation (CV)0.71421689
Kurtosis2.2788555
Mean0.030538498
Median Absolute Deviation (MAD)0.01162
Skewness1.4667239
Sum29.042112
Variance0.00047572457
MonotonicityNot monotonic
2023-03-31T16:40:34.491884image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01424 3
 
0.3%
0.00633 3
 
0.3%
0.0261 3
 
0.3%
0.01284 3
 
0.3%
0.00469 2
 
0.2%
0.02687 2
 
0.2%
0.01604 2
 
0.2%
0.01685 2
 
0.2%
0.01908 2
 
0.2%
0.02892 2
 
0.2%
Other values (862) 927
97.5%
ValueCountFrequency (%)
0.00335 1
0.1%
0.00455 1
0.1%
0.00468 1
0.1%
0.00469 2
0.2%
0.00476 1
0.1%
0.00482 1
0.1%
0.0049 1
0.1%
0.00504 1
0.1%
0.00522 2
0.2%
0.00534 1
0.1%
ValueCountFrequency (%)
0.13051 1
0.1%
0.12801 1
0.1%
0.12428 1
0.1%
0.11716 1
0.1%
0.11714 1
0.1%
0.10554 1
0.1%
0.10436 1
0.1%
0.10336 1
0.1%
0.1023 1
0.1%
0.10229 1
0.1%

Shimmer:APQ5
Real number (ℝ)

Distinct881
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.036397877
Minimum0.00415
Maximum0.19951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:34.606733image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.00415
5-th percentile0.009185
Q10.01781
median0.02886
Q30.04731
95-th percentile0.090165
Maximum0.19951
Range0.19536
Interquartile range (IQR)0.0295

Descriptive statistics

Standard deviation0.026543249
Coefficient of variation (CV)0.72925267
Kurtosis3.965391
Mean0.036397877
Median Absolute Deviation (MAD)0.01367
Skewness1.7230251
Sum34.614381
Variance0.00070454406
MonotonicityNot monotonic
2023-03-31T16:40:34.706813image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01003 3
 
0.3%
0.04669 2
 
0.2%
0.02001 2
 
0.2%
0.00898 2
 
0.2%
0.04754 2
 
0.2%
0.02886 2
 
0.2%
0.02947 2
 
0.2%
0.01866 2
 
0.2%
0.01692 2
 
0.2%
0.03672 2
 
0.2%
Other values (871) 930
97.8%
ValueCountFrequency (%)
0.00415 1
0.1%
0.0057 1
0.1%
0.00576 1
0.1%
0.00582 1
0.1%
0.00588 1
0.1%
0.00606 1
0.1%
0.0061 1
0.1%
0.00621 1
0.1%
0.0063 1
0.1%
0.00631 1
0.1%
ValueCountFrequency (%)
0.19951 1
0.1%
0.15668 1
0.1%
0.15058 1
0.1%
0.14695 1
0.1%
0.14476 1
0.1%
0.14372 1
0.1%
0.14017 1
0.1%
0.13917 1
0.1%
0.13676 1
0.1%
0.1354 1
0.1%

Shimmer:DDA
Real number (ℝ)

Distinct923
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.091615463
Minimum0.01004
Maximum0.39154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:34.823316image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.01004
5-th percentile0.022665
Q10.043605
median0.07372
Q30.119905
95-th percentile0.22798
Maximum0.39154
Range0.3815
Interquartile range (IQR)0.0763

Descriptive statistics

Standard deviation0.065433021
Coefficient of variation (CV)0.71421372
Kurtosis2.2788766
Mean0.091615463
Median Absolute Deviation (MAD)0.03487
Skewness1.4667125
Sum87.126306
Variance0.0042814803
MonotonicityNot monotonic
2023-03-31T16:40:34.924778image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01898 3
 
0.3%
0.103247815 2
 
0.2%
0.05373 2
 
0.2%
0.02849 2
 
0.2%
0.08061 2
 
0.2%
0.05056 2
 
0.2%
0.02774 2
 
0.2%
0.1053 2
 
0.2%
0.0827 2
 
0.2%
0.03191 2
 
0.2%
Other values (913) 930
97.8%
ValueCountFrequency (%)
0.01004 1
0.1%
0.01364 1
0.1%
0.01403 1
0.1%
0.01406 1
0.1%
0.01407 1
0.1%
0.01428 1
0.1%
0.01445 1
0.1%
0.01471 1
0.1%
0.01513 1
0.1%
0.01567 2
0.2%
ValueCountFrequency (%)
0.39154 1
0.1%
0.38404 1
0.1%
0.37283 1
0.1%
0.35147 1
0.1%
0.35142 1
0.1%
0.31663 1
0.1%
0.31309 1
0.1%
0.31007 1
0.1%
0.30689 1
0.1%
0.30688 1
0.1%

NHR
Real number (ℝ)

Distinct931
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.045741857
Minimum0.000618
Maximum0.761696
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:35.060793image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.000618
5-th percentile0.002632
Q10.00679
median0.015435
Q30.035533
95-th percentile0.213139
Maximum0.761696
Range0.761078
Interquartile range (IQR)0.028743

Descriptive statistics

Standard deviation0.095594323
Coefficient of variation (CV)2.0898654
Kurtosis23.164602
Mean0.045741857
Median Absolute Deviation (MAD)0.01019
Skewness4.4600386
Sum43.500506
Variance0.0091382745
MonotonicityNot monotonic
2023-03-31T16:40:35.172252image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00681 2
 
0.2%
0.00623 2
 
0.2%
0.0042 2
 
0.2%
0.001613 2
 
0.2%
0.005904 2
 
0.2%
0.020172 2
 
0.2%
0.002908 2
 
0.2%
0.00626 2
 
0.2%
0.0062 2
 
0.2%
0.00839 2
 
0.2%
Other values (921) 931
97.9%
ValueCountFrequency (%)
0.000618 1
0.1%
0.00065 1
0.1%
0.00072 1
0.1%
0.00119 1
0.1%
0.001264 1
0.1%
0.001267 1
0.1%
0.001309 1
0.1%
0.00135 1
0.1%
0.001369 1
0.1%
0.001479 1
0.1%
ValueCountFrequency (%)
0.761696 1
0.1%
0.749908 1
0.1%
0.737512 1
0.1%
0.726743 1
0.1%
0.657229 1
0.1%
0.655696 1
0.1%
0.638835 1
0.1%
0.617838 1
0.1%
0.611854 1
0.1%
0.566703 1
0.1%

HNR
Real number (ℝ)

Distinct931
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.480176
Minimum1.655
Maximum33.197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:35.291196image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1.655
5-th percentile9.074
Q116.605
median20.079
Q323.322
95-th percentile26.9705
Maximum33.197
Range31.542
Interquartile range (IQR)6.717

Descriptive statistics

Standard deviation5.4962164
Coefficient of variation (CV)0.28214409
Kurtosis0.54038029
Mean19.480176
Median Absolute Deviation (MAD)3.356
Skewness-0.66163253
Sum18525.647
Variance30.208395
MonotonicityNot monotonic
2023-03-31T16:40:35.396997image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.954 2
 
0.2%
17.507 2
 
0.2%
25.175 2
 
0.2%
18.781 2
 
0.2%
24.058 2
 
0.2%
23.336 2
 
0.2%
16.515 2
 
0.2%
20.075 2
 
0.2%
18.344 2
 
0.2%
17.215 2
 
0.2%
Other values (921) 931
97.9%
ValueCountFrequency (%)
1.655 1
0.1%
1.671 1
0.1%
1.751 1
0.1%
1.995 1
0.1%
2.134 1
0.1%
2.251 1
0.1%
2.435 1
0.1%
2.72 1
0.1%
3.013 1
0.1%
3.273 1
0.1%
ValueCountFrequency (%)
33.197 1
0.1%
33.047 1
0.1%
32.684 1
0.1%
31.732 1
0.1%
30.948 1
0.1%
30.94 1
0.1%
30.801 1
0.1%
30.775 1
0.1%
30.662 1
0.1%
29.928 1
0.1%

RPDE
Real number (ℝ)

Distinct942
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49100103
Minimum0.1543
Maximum0.87123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:35.514748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.1543
5-th percentile0.283035
Q10.39291
median0.48686
Q30.58666
95-th percentile0.698635
Maximum0.87123
Range0.71693
Interquartile range (IQR)0.19375

Descriptive statistics

Standard deviation0.13127776
Coefficient of variation (CV)0.26736758
Kurtosis-0.39806462
Mean0.49100103
Median Absolute Deviation (MAD)0.09709
Skewness0.14504933
Sum466.94198
Variance0.017233849
MonotonicityNot monotonic
2023-03-31T16:40:35.607443image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.42171 2
 
0.2%
0.62128 2
 
0.2%
0.36909 2
 
0.2%
0.70689 2
 
0.2%
0.45816 2
 
0.2%
0.42443 2
 
0.2%
0.6425 2
 
0.2%
0.38853 2
 
0.2%
0.34552 2
 
0.2%
0.47213 1
 
0.1%
Other values (932) 932
98.0%
ValueCountFrequency (%)
0.1543 1
0.1%
0.17873 1
0.1%
0.18984 1
0.1%
0.19559 1
0.1%
0.20569 1
0.1%
0.20677 1
0.1%
0.20724 1
0.1%
0.20741 1
0.1%
0.21063 1
0.1%
0.21349 1
0.1%
ValueCountFrequency (%)
0.87123 1
0.1%
0.8498 1
0.1%
0.84808 1
0.1%
0.8475 1
0.1%
0.83478 1
0.1%
0.83083 1
0.1%
0.82679 1
0.1%
0.81928 1
0.1%
0.81889 1
0.1%
0.81817 1
0.1%

DFA
Real number (ℝ)

Distinct940
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.70404023
Minimum0.5435
Maximum0.85264
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:35.715460image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.5435
5-th percentile0.58994
Q10.65249
median0.70443
Q30.757005
95-th percentile0.81406
Maximum0.85264
Range0.30914
Interquartile range (IQR)0.104515

Descriptive statistics

Standard deviation0.06737389
Coefficient of variation (CV)0.09569608
Kurtosis-0.73911299
Mean0.70404023
Median Absolute Deviation (MAD)0.05237
Skewness-0.069227362
Sum669.54225
Variance0.004539241
MonotonicityNot monotonic
2023-03-31T16:40:35.810299image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.80616 2
 
0.2%
0.75192 2
 
0.2%
0.72248 2
 
0.2%
0.80358 2
 
0.2%
0.76831 2
 
0.2%
0.65177 2
 
0.2%
0.67496 2
 
0.2%
0.67512 2
 
0.2%
0.67772 2
 
0.2%
0.75399 2
 
0.2%
Other values (930) 931
97.9%
ValueCountFrequency (%)
0.5435 1
0.1%
0.54532 1
0.1%
0.55221 1
0.1%
0.5532 1
0.1%
0.55398 1
0.1%
0.55428 1
0.1%
0.55586 1
0.1%
0.56003 1
0.1%
0.56036 1
0.1%
0.56078 1
0.1%
ValueCountFrequency (%)
0.85264 1
0.1%
0.85123 1
0.1%
0.8507 1
0.1%
0.85 1
0.1%
0.84019 1
0.1%
0.8384 1
0.1%
0.83764 1
0.1%
0.83561 1
0.1%
0.83549 1
0.1%
0.83305 1
0.1%

PPE
Real number (ℝ)

Distinct935
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6356135
Minimum0.041551
Maximum0.90766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-03-31T16:40:35.923543image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.041551
5-th percentile0.131141
Q10.374195
median0.79196
Q30.82754
95-th percentile0.856045
Maximum0.90766
Range0.866109
Interquartile range (IQR)0.453345

Descriptive statistics

Standard deviation0.26827312
Coefficient of variation (CV)0.42206958
Kurtosis-0.80937528
Mean0.6356135
Median Absolute Deviation (MAD)0.05189
Skewness-0.95872434
Sum604.46844
Variance0.071970469
MonotonicityNot monotonic
2023-03-31T16:40:36.032573image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.82273 3
 
0.3%
0.83125 2
 
0.2%
0.83918 2
 
0.2%
0.8088 2
 
0.2%
0.79132 2
 
0.2%
0.79067 2
 
0.2%
0.7993 2
 
0.2%
0.81783 2
 
0.2%
0.79855 2
 
0.2%
0.79196 2
 
0.2%
Other values (925) 930
97.8%
ValueCountFrequency (%)
0.041551 1
0.1%
0.044539 1
0.1%
0.056141 1
0.1%
0.05761 1
0.1%
0.068501 1
0.1%
0.073581 1
0.1%
0.075587 1
0.1%
0.084429 1
0.1%
0.085569 1
0.1%
0.086398 1
0.1%
ValueCountFrequency (%)
0.90766 1
0.1%
0.89604 1
0.1%
0.88763 1
0.1%
0.88663 1
0.1%
0.88492 1
0.1%
0.88389 1
0.1%
0.88352 1
0.1%
0.87911 1
0.1%
0.87793 1
0.1%
0.87601 1
0.1%

status
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
1
711 
0
240 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters951
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 711
74.8%
0 240
 
25.2%

Length

2023-03-31T16:40:36.134519image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-31T16:40:36.203890image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
1 711
74.8%
0 240
 
25.2%

Most occurring characters

ValueCountFrequency (%)
1 711
74.8%
0 240
 
25.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 951
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 711
74.8%
0 240
 
25.2%

Most occurring scripts

ValueCountFrequency (%)
Common 951
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 711
74.8%
0 240
 
25.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 711
74.8%
0 240
 
25.2%

Interactions

2023-03-31T16:40:29.867216image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:51.682392image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:54.581723image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:57.773112image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:02.058017image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:05.459415image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:08.610998image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:11.421997image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:13.794828image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:16.367511image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:18.687258image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:20.957688image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:23.473145image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:25.481978image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:27.787266image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:29.986826image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:51.827639image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:54.788526image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:58.012163image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:02.261646image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:05.689038image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:08.859684image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:11.550542image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:13.993355image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:16.499742image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:18.826755image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:21.102159image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:23.611851image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:25.597162image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:27.922008image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:30.144983image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:51.977851image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:54.951018image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:39:59.315626image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:02.525610image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:05.897323image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:09.077010image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
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2023-03-31T16:40:23.052393image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2023-03-31T16:40:25.113841image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
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2023-03-31T16:40:29.738650image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Correlations

2023-03-31T16:40:36.285547image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Jitter(%)Jitter(Abs)Jitter:RAPJitter:PPQJitter:DDPShimmerShimmer(dB)Shimmer:APQ3Shimmer:APQ5Shimmer:DDANHRHNRRPDEDFAPPEstatus
Jitter(%)1.0000.9710.9590.9680.9590.1120.1340.0990.1000.0990.524-0.3910.5950.301-0.6370.181
Jitter(Abs)0.9711.0000.9490.9680.9490.1310.1480.1180.1180.1180.523-0.3920.6220.324-0.5870.159
Jitter:RAP0.9590.9491.0000.9841.0000.0750.0960.0800.0650.0800.493-0.3620.5470.340-0.6800.137
Jitter:PPQ0.9680.9680.9841.0000.9840.1310.1500.1260.1210.1260.540-0.4170.5940.353-0.6300.186
Jitter:DDP0.9590.9491.0000.9841.0000.0750.0950.0800.0650.0800.493-0.3620.5470.340-0.6790.137
Shimmer0.1120.1310.0750.1310.0751.0000.9970.9840.9920.9840.723-0.7990.4930.2150.1540.258
Shimmer(dB)0.1340.1480.0960.1500.0950.9971.0000.9780.9870.9780.736-0.8050.5010.2250.1300.278
Shimmer:APQ30.0990.1180.0800.1260.0800.9840.9781.0000.9771.0000.710-0.7920.4580.2450.1480.222
Shimmer:APQ50.1000.1180.0650.1210.0650.9920.9870.9771.0000.9770.710-0.7950.4780.2220.1640.190
Shimmer:DDA0.0990.1180.0800.1260.0800.9840.9781.0000.9771.0000.710-0.7920.4580.2450.1480.222
NHR0.5240.5230.4930.5400.4930.7230.7360.7100.7100.7101.000-0.9450.7450.191-0.2010.067
HNR-0.391-0.392-0.362-0.417-0.362-0.799-0.805-0.792-0.795-0.792-0.9451.000-0.680-0.2300.0620.262
RPDE0.5950.6220.5470.5940.5470.4930.5010.4580.4780.4580.745-0.6801.0000.092-0.3120.265
DFA0.3010.3240.3400.3530.3400.2150.2250.2450.2220.2450.191-0.2300.0921.000-0.1410.299
PPE-0.637-0.587-0.680-0.630-0.6790.1540.1300.1480.1640.148-0.2010.062-0.312-0.1411.0000.268
status0.1810.1590.1370.1860.1370.2580.2780.2220.1900.2220.0670.2620.2650.2990.2681.000

Missing values

2023-03-31T16:40:31.812082image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-31T16:40:32.048713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

nameJitter(%)Jitter(Abs)Jitter:RAPJitter:PPQJitter:DDPShimmerShimmer(dB)Shimmer:APQ3Shimmer:APQ5Shimmer:DDANHRHNRRPDEDFAPPEstatus
0phon_R01_S01_10.007840.000070.003700.005540.011090.043740.4260.021820.031300.065450.0221121.0330.4147830.8152850.2846541
1phon_R01_S01_20.009680.000080.004650.006960.013940.061340.6260.031340.045180.094030.0192919.0850.4583590.8195210.3686741
2phon_R01_S01_30.010500.000090.005440.007810.016330.052330.4820.027570.038580.082700.0130920.6510.4298950.8252880.3326341
3phon_R01_S01_40.009970.000090.005020.006980.015050.054920.5170.029240.040050.087710.0135320.6440.4349690.8192350.3689751
4phon_R01_S01_50.012840.000110.006550.009080.019660.064250.5840.034900.048250.104700.0176719.6490.4173560.8234840.4103351
5phon_R01_S01_60.009680.000080.004630.007500.013880.047010.4560.023280.035260.069850.0122221.3780.4155640.8250690.3577751
6phon_R01_S02_10.003330.000030.001550.002020.004660.016080.1400.007790.009370.023370.0060724.8860.5960400.7641120.2117561
7phon_R01_S02_20.002900.000030.001440.001820.004310.015670.1340.008290.009460.024870.0034426.8920.6374200.7632620.1637551
8phon_R01_S02_30.005510.000060.002930.003320.008800.020930.1910.010730.012770.032180.0107021.8120.6155510.7735870.2315711
9phon_R01_S02_40.005320.000060.002680.003320.008030.028380.2550.014410.017250.043240.0102221.8620.5470370.7984630.2713621
nameJitter(%)Jitter(Abs)Jitter:RAPJitter:PPQJitter:DDPShimmerShimmer(dB)Shimmer:APQ3Shimmer:APQ5Shimmer:DDANHRHNRRPDEDFAPPEstatus
9412480.003130.0000170.000890.001040.002680.091170.8670.048760.054990.146290.04613214.1510.423890.675120.831101
9422490.000770.0000040.000150.000330.000440.098920.8760.055780.059350.167340.00701022.0380.428900.782310.851411
9432490.000840.0000050.000120.000290.000360.021210.1840.011570.013910.034710.00510323.4650.363420.787720.796451
9442490.000790.0000050.000140.000340.000430.037370.3320.021100.024130.063290.00521023.3080.328240.796370.811711
9452500.000880.0000050.000120.000330.000370.018340.1600.009770.011410.029320.00510023.6970.360170.578490.831720
9462500.000640.0000030.000080.000220.000240.019470.1710.010680.012600.032040.00257126.8130.283850.563550.809030
9472500.001430.0000060.000160.000410.000470.042910.4820.023070.026260.069200.02551917.8020.591940.564990.160840
9482510.000760.0000040.000110.000300.000340.029780.2630.015970.019160.047900.00448024.0050.468150.723350.883890
9492510.000920.0000050.000170.000410.000520.035520.3110.017910.023480.053730.01193119.7060.498230.748900.837820
9502510.000780.0000040.000140.000330.000420.037020.3260.019400.023320.058200.00361525.2760.463740.764710.813040

Duplicate rows

Most frequently occurring

nameJitter(%)Jitter(Abs)Jitter:RAPJitter:PPQJitter:DDPShimmerShimmer(dB)Shimmer:APQ3Shimmer:APQ5Shimmer:DDANHRHNRRPDEDFAPPEstatus# duplicates
0370.002070.0000120.000290.000740.000860.045750.4110.017850.027630.053560.01712618.7810.64250.584650.7906712